Semiconductor integrated circuits are produced by a plurality of processes in a wafer fabrication facility (fab). As examples, these processes may include thermal oxidation, diffusion, ion implantation, rapid thermal processing (RTP), chemical vapor deposition (CVD), physical vapor deposition (PVD), epitaxy, etch, and photolithography. As performance requirements and throughput demands increase, semiconductor fabrication process control has become increasingly crucial. However, as process geometries decrease, it may be challenging to keep process variations at acceptable levels. As such, the processes may suffer from losses in tool productivity, increased operator interaction, yield loss, and higher rework rates, all possibly leading to higher costs.
Advanced Process Control (APC), which may include models and feedback systems among other process control techniques, has been widely used to help alleviate some of the variations. It is also desirable to utilize APC techniques to establish models and use these models to predict process performance. However, existing APC techniques may suffer from shortcomings such as heavy dependence on human input and manual calculations, inaccurate predictions, and the need for multiple model revisions. These shortcomings tend to cause delay in the manufacturing process and therefore increases fabrication costs.
Consequently, although existing APC techniques have been generally adequate for their intended purposes, they have not been entirely satisfactory in all respects.